For example, if your data is in a CSV file, use the appropriate method from the imported library to load the data into a DataFrame or a NumPy array. Step 3: Sorting the Data: Once the data is loaded, you can now use the 'ascending' parameter to sort the data in the desired order...
You can sorting rows by numpy.sort, swap ordering for descending order by [:, ::-1] and pass to DataFrame constructor if performance is important: #10k rows df = pd.concat([df] * 1000, ignore_index=True) #Ynjxsjmh sol In [200]: %timeit df.apply(lambda row: list(reversed(sorted(...
For example, if your data is in a CSV file, use the appropriate method from the imported library to load the data into a DataFrame or a NumPy array. Step 3: Sorting the Data: Once the data is loaded, you can now use the 'ascending' parameter to sort the data in the desired order...